Certain aspects of the present disclosure provide techniques for generating an insight, comprising: receiving a request to generate an insight for a document from a user associated with the document; receiving the document; generating a tree based on the document; parsing the tree based on a set of rules to generate a set of results associated with the tree; mapping the set of results to a subset of insight elements of a set of insight elements associated with a set of trees including the tree; providing, to a first machine-learning model, the subset of insight elements; receiving, from the first machine-learning model, an insight for the document based on the subset of insight elements; and returning the insight for the document to the user.
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3. The method of claim 1, wherein the document is associated with an organization, wherein the health score for the document indicates a probability of the organization being in operation during a time period.
5. The method of claim 1, wherein receiving the set of rules and the set of insight elements comprises receiving the set of rules and set of insight elements from a computing device associated with an expert associated with the set of historical documents.
This invention relates to a system for analyzing historical documents to generate insights using expert-defined rules. The problem addressed is the difficulty in automatically extracting meaningful insights from large volumes of historical documents without expert guidance. The solution involves a method where a computing system receives a set of rules and a set of insight elements from a computing device associated with an expert familiar with the historical documents. The rules define criteria for identifying relevant information, while the insight elements represent the types of insights to be extracted. The system then processes the historical documents according to these rules to generate insights, which are then presented to users. The method ensures that the analysis is tailored to the expert's knowledge, improving the accuracy and relevance of the extracted insights. The system may also allow for iterative refinement of the rules and insight elements based on user feedback or additional expert input. This approach enhances the efficiency of document analysis by leveraging expert knowledge to guide automated processing.
8. The system of claim 6, wherein the document is associated with an organization, wherein the health score for the document indicates a probability of the organization being in operation during a time period.
10. The system of claim 6, wherein receiving the set of rules and the set of insight elements comprises receiving the set of rules and set of insight elements from a computing device associated with an expert associated with the set of historical documents.
13. The non-transitory computer-readable medium of claim 11, wherein the document is associated with an organization, wherein the health score for the document indicates a probability of the organization being in operation during a time period.
This invention relates to systems for assessing the operational status of organizations based on document analysis. The technology addresses the challenge of determining whether an organization is still active or has ceased operations, which is critical for business intelligence, compliance, and risk assessment. The system analyzes documents associated with an organization to generate a health score, which quantifies the likelihood that the organization remains operational during a specified time period. The health score is derived from various document attributes, such as recency, relevance, and frequency of updates, which serve as indicators of organizational activity. The system processes these attributes using computational models to produce a probabilistic assessment of the organization's operational status. This approach enables automated monitoring of organizational health without requiring direct verification, improving efficiency and accuracy in tracking business entities. The invention is particularly useful in fields like financial services, regulatory compliance, and market research, where knowing the operational status of organizations is essential for decision-making. By leveraging document-based analysis, the system provides a scalable and data-driven method for assessing organizational viability.
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March 31, 2021
November 15, 2022
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